AI in Predictive Analysis of Purchasing Behavior: Accuracy, Ethics, and Acceptability.

In a world where digital data is central to marketing strategies, artificial intelligence (AI) offers enhanced capabilities to analyze, predict, and influence consumer purchasing behavior. Using advanced machine learning and deep learning techniques, companies can anticipate consumer actions and tailor their offers to maximize engagement and conversion. However, the integration of these technologies raises ethical concerns and questions about consumer acceptability. The accuracy of algorithms can also pose challenges, particularly in terms of potential biases and data privacy.

This research explores three essential dimensions:

• The accuracy of AI models in predicting purchasing behaviors.
• The ethical aspects of personal data use and personalized recommendations.
• The acceptability of these practices among Moroccan consumers, focusing on their perceptions, privacy concerns, and trust in companies using AI.

Theoretical Approaches

The research will draw on several key theoretical frameworks:

• Expected Utility Theory : This framework will help analyze how consumers perceive the risks and benefits of AI-driven personalized recommendations. It will specifically assist in examining consumer preferences and risk tolerance regarding personal data usage.
• Privacy Calculus Theory: This model examines how individuals weigh the costs and benefits of disclosing personal information. By using it, we will evaluate the extent to which Moroccan consumers are willing to exchange their privacy for personalized shopping experiences.
• Ethics of Responsibility: This theory will assist in analyzing the moral and ethical issues related to the use of AI in marketing, including transparency, fairness, and non-discrimination in predictive algorithms.
• Technology Acceptance Model (TAM): This model will be used to measure consumer acceptability and adherence to predictive technologies powered by AI. It will be enriched to incorporate ethical and privacy dimensions.

Epistemological Positioning

This research adopts an interpretivist epistemological stance , assuming that Moroccan consumers' perceptions and attitudes toward AI in marketing are influenced by their individual experiences and sociocultural contexts. This approach will provide an in-depth and nuanced understanding of the psychological, social, and ethical factors that shape the acceptability of AI in marketing.

Methodological Approaches

This study will employ a mixed-methods methodology:

• Quantitative Approach : A structured survey will be administered to a representative sample of Moroccan consumers to measure their perceptions of accuracy, ethical issues, and the acceptability of AI in marketing. This survey will include Likert scales to assess attitudes and comfort levels with data collection and usage for marketing purposes.
• Qualitative Approach : In-depth interviews will be conducted with Moroccan consumers to explore their perceptions, concerns, and expectations regarding privacy, ethics, and the utility of predictive technologies. These interviews will allow the collection of rich, contextual data that will complement the quantitative findings.
• Case Studies with Moroccan Companies : We will examine companies using AI-driven predictive marketing tools to understand how they implement these technologies, manage ethical issues, and address the acceptability of their practices.

Study Setting

The study setting is focused on the Moroccan market , involving a broad sample of consumers from different regions to obtain a diversified view of perceptions. The qualitative interviews and case studies will also include Moroccan companies from sectors such as retail, e-commerce, and banking that use AI models to anticipate and influence purchasing behaviors.

Artificial Intelligence

Predictive Analysis

Purchasing Behavior

Ethics in Marketing

AI Acceptability

Privacy

Consumer

Master's degree / 5-year post-secondary degree in Management Sciences (specializing in Marketing)

Deadline to send the application: November 11, 2024

Cedoc.admission@ueuromed.org & o.benjelloun@ueuromed.org 

Prof. Omar BENJELLOUN ANDALOUSSI